Efficient execution of large-scale scientific applications requires high-performance
computing systems designed to meet the I/O requirements. Most I/O- and data-intensive
parallel applications access multiple layers in the I/O stack during the operations. Typ-
ical I/O requests from these applications may include accesses to high-level I/O libraries
such as Parallel netCDF and HDF5, the MPI I/O library, and parallel file systems such
as PVFS, in turn supported by native file systems in Linux. To design and implement
parallel applications that exercise this I/O stack, one must understand the flow and in-
teraction of I/O calls through the entire I/O stack. Such understanding helps identify
I/O bottlenecks and thus exploit the potential performance in different layers of the
storage hierarchy. To trace the execution of I/O calls and to understand the complex
interactions among multiple user libraries and file systems, we implement a GUI-based
integrated profiling and analysis environment, PAVIS. Our implementation automati-
cally generates an instrumented I/O stack, runs applications, and visualizes detailed
statistics in terms of user-specified metrics of interest.
